We are looking for a Senior Data Analytics Engineer to help shape and scale modern data capabilities for a real estate and property organization in Reston, Virginia. This role focuses on designing reliable data pipelines, structuring analytical datasets, and enabling high-quality reporting and advanced insights across the business. The ideal candidate brings strong engineering depth, practical analytics expertise, and the ability to turn business needs into well-architected data solutions. Responsibilities: • Design, build, and maintain scalable data pipelines that ingest, transform, and deliver trusted datasets for analytics and operational use. • Develop curated data layers using medallion-style architecture to improve data quality, accessibility, and consistency across the platform. • Create and optimize dimensional models, including fact and dimension structures, to support reporting, trend analysis, and business intelligence needs. • Use Python, PySpark, SparkSQL, and notebook-based development environments to engineer efficient data processing workflows. • Partner with business and technical stakeholders to gather requirements and translate them into practical data products and analytics solutions. • Apply data governance, security, and enterprise data management standards to protect information and support compliant data usage. • Contribute to collaborative development practices through version control, code review, and shared engineering standards using Git. • Support advanced analytics initiatives by preparing data foundations that can be used for machine learning and AI-driven use cases.

• At least 5 years of experience in data engineering, analytics engineering, or a comparable data-centric role. • Demonstrated expertise in dimensional modeling, including the design of fact tables, dimension tables, and slowly changing dimensions. • Strong hands-on capability with Python, PySpark, SparkSQL, and notebook-based data development. • Experience delivering end-to-end data solutions built on medallion architecture principles. • Working knowledge of modern big data technologies such as Apache Spark, Hadoop, Kafka, and ETL frameworks. • Familiarity with machine learning and AI concepts within contemporary analytics environments. • Experience using Git within team-based software or data development workflows. • Strong communication skills with the ability to align technical delivery with business objectives.

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Herndon, VA
onsite
Permanent / Full Time
140000 - 150000 USD / Yearly
We are looking for a Senior Data Analytics Engineer to help shape and scale modern data capabilities for a real estate and property organization in Reston, Virginia. This role focuses on designing reliable data pipelines, structuring analytical datasets, and enabling high-quality reporting and advanced insights across the business. The ideal candidate brings strong engineering depth, practical analytics expertise, and the ability to turn business needs into well-architected data solutions. Responsibilities: • Design, build, and maintain scalable data pipelines that ingest, transform, and deliver trusted datasets for analytics and operational use. • Develop curated data layers using medallion-style architecture to improve data quality, accessibility, and consistency across the platform. • Create and optimize dimensional models, including fact and dimension structures, to support reporting, trend analysis, and business intelligence needs. • Use Python, PySpark, SparkSQL, and notebook-based development environments to engineer efficient data processing workflows. • Partner with business and technical stakeholders to gather requirements and translate them into practical data products and analytics solutions. • Apply data governance, security, and enterprise data management standards to protect information and support compliant data usage. • Contribute to collaborative development practices through version control, code review, and shared engineering standards using Git. • Support advanced analytics initiatives by preparing data foundations that can be used for machine learning and AI-driven use cases.
2026-06-02T00:00:00Z